AIMC Topic: Follow-Up Studies
Clear Filters Showing 301 to 310 of 750 articles
Exercise cardiac power and the risk of heart failure in men: A population-based follow-up study.
Journal of sport and health science
Feb 24, 2020
BACKGROUND: Little is known about exercise cardiac power (ECP), defined as the ratio of directly measured maximal oxygen uptake with peak systolic blood pressure during exercise, on heart failure (HF) risk. We examined the association of ECP and the ...
Accelerated coronary MRI with sRAKI: A database-free self-consistent neural network k-space reconstruction for arbitrary undersampling.
PloS one
Feb 21, 2020
PURPOSE: To accelerate coronary MRI acquisitions with arbitrary undersampling patterns by using a novel reconstruction algorithm that applies coil self-consistency using subject-specific neural networks.
A comparison of fMRI and behavioral models for predicting inter-temporal choices.
NeuroImage
Feb 18, 2020
In an inter-temporal choice (IteCh) task, subjects are offered a smaller amount of money immediately or a larger amount at a later time point. Here, we are using trial-by-trial fMRI data from 363 recording sessions and machine learning in an attempt ...
Assessing and Mitigating Bias in Medical Artificial Intelligence: The Effects of Race and Ethnicity on a Deep Learning Model for ECG Analysis.
Circulation. Arrhythmia and electrophysiology
Feb 16, 2020
BACKGROUND: Deep learning algorithms derived in homogeneous populations may be poorly generalizable and have the potential to reflect, perpetuate, and even exacerbate racial/ethnic disparities in health and health care. In this study, we aimed to (1)...
A Deep Learning Model for Segmentation of Geographic Atrophy to Study Its Long-Term Natural History.
Ophthalmology
Feb 15, 2020
PURPOSE: To develop and validate a deep learning model for the automatic segmentation of geographic atrophy (GA) using color fundus images (CFIs) and its application to study the growth rate of GA.
Identifying treatment effects of an informal caregiver education intervention to increase days in the community and decrease caregiver distress: a machine-learning secondary analysis of subgroup effects in the HI-FIVES randomized clinical trial.
Trials
Feb 14, 2020
BACKGROUND: Informal caregivers report substantial burden and depressive symptoms which predict higher rates of patient institutionalization. While caregiver education interventions may reduce caregiver distress and decrease the use of long-term inst...
Middle Aged
Quality of Life
Depression
Stress, Psychological
Cognitive Dysfunction
Female
Aged
Aged, 80 and over
Male
Veterans
Family
Caregivers
Institutionalization
Long-Term Care
Treatment Outcome
Follow-Up Studies
Age Factors
Randomized Controlled Trials as Topic
Data Interpretation, Statistical
Humans
Machine Learning
Comparison of medium-term survival outcomes between robot-assisted thoracoscopic surgery and video-assisted thoracoscopic surgery in treating primary lung cancer.
General thoracic and cardiovascular surgery
Feb 13, 2020
OBJECTIVES: Robot-assisted thoracoscopic surgery (RATS) for primary lung cancer has been spreading rapidly in Japan. While RATS has various technical advantages over video-assisted thoracoscopic surgery (VATS), the quality of surgery from an oncologi...
Predicting 10-Year Risk of End-Organ Complications of Type 2 Diabetes With and Without Metabolic Surgery: A Machine Learning Approach.
Diabetes care
Feb 6, 2020
OBJECTIVE: To construct and internally validate prediction models to estimate the risk of long-term end-organ complications and mortality in patients with type 2 diabetes and obesity that can be used to inform treatment decisions for patients and pra...
Melanoma recognition by a deep learning convolutional neural network-Performance in different melanoma subtypes and localisations.
European journal of cancer (Oxford, England : 1990)
Jan 20, 2020
BACKGROUND: Deep learning convolutional neural networks (CNNs) show great potential for melanoma diagnosis. Melanoma thickness at diagnosis among others depends on melanoma localisation and subtype (e.g. advanced thickness in acrolentiginous or nodul...
Prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer using a deep learning (DL) method.
Thoracic cancer
Jan 16, 2020
BACKGROUND: The aim of the study was to develop a deep learning (DL) algorithm to evaluate the pathological complete response (pCR) to neoadjuvant chemotherapy in breast cancer.
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31059
- Neural Networks, Computer 29727
- Algorithms 26848
- Deep Learning 26366
- Artificial Intelligence 24311
- Robotics 13314
- Image Processing, Computer-Assisted 9527
- Retrospective Studies 9114
- Magnetic Resonance Imaging 6186
- Reproducibility of Results 5593
- Tomography, X-Ray Computed 4772
- Support Vector Machine 4688
- Computational Biology 4240
- Brain 4053
- Computer Simulation 3882
Recent Journals
- Scientific reports 5971
- Sensors (Basel, Switzerland) 4794
- PloS one 4022
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1860
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1131
- Journal of chemical information and modeling 1000
- Nature communications 949
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 826